NURINNAFISA BINTI MOHAMAD ZAKI's profile picture NURINNAFISA BINTI MOHAMAD ZAKI

Member of elearning.utm.my

NURINNAFISA BINTI MOHAMAD ZAKI's Reflection RSS

Lecture 5-Areal Data Analysis

The last topic that I learn is areal data analysis. In this topic I learn about moran’s l autocorrelation, Geary’s C autocorrelation, and Joint count statistic. All the autocorrelation is important in our life because we use it every day. For joint count, it is a simplest way of quantitatively measuring spatial autocorrelation for a set of spatially adjacent polygons. It used black and white, black black, or white white. Moran mainly used for interval or ratio type of data, and it is a easiest way to solve is by using spatial weighted matrix it also used hypothesis testing. Last but not least, geary’s c. It same as Moran’s l. it also used hypothesis testing at the last calculation and have the little bit different with moran.

Lecture 4-Line Data Analysis

The second last topic that my lecturer teach is line data analysis. In this topic, I learn about network data and graph, branching network, circuit network, elementary graph theory measures, network connectivity, and network accessibility. In this topic, I learn more about the line of connection and why the connection is important in our life. Other than that, I learn about the branching network, and how to calculate the connection by the given formula. It shows that to know the connections, we should know the formula to calculate the total connections and with road is good for us to use. That is why network accessibility is important.

Lecture 3-Point Data Analysis

For topic 3, I learn about point data analysis. In this topic, I learn about spatial density, centography, and, pattern. Point can be categorized into 3 which is density (simple density, sampling density), centography (mean center, weighted mean center, and standard distance), and pattern (quadrat analysis, and nearest neighbour analysis). Mean center is the mean of x and y coordinates for a set of points. Centography is spatial equivalent for conventional descriptive statistic. Weighted mean center is produced by weighting each x and y coordinate by another variable. Besides that, I also study about quadrat analysis which so useful for finding out point pattern.

Lecture 2-Sampling Theory

Next topic, I learn about sampling method. In this topic, I will learn about population, sample and other statistical, types of variables, and the theory of sampling. In the topic about population, I learn more about the meaning of population, sample, variable, and random variable. I also learn about parameter, statistic, probability, and distribution. Other than that, I also know that there were 2 types of samples which is independent sample and dependent sample. Independent sample is when member of the sample is not related to others member while dependent means each member of one sample is paired with a member of the other sample. There also have types of variables which is qualitative and quantitative. Qualitative can be placed into distinct categories, according to some characteristic or attribute. For example, gender while quantitative is numerical and can be ordered or ranked for example age. Next, I also learn about types of sampling that had 2 types which is probability, and non-probability. Probability has four types. For example, simple random, stratified random, random systematic, and cluster random while probability have one which is convenience.   

Lecture 1-Introduction to Spatial Statistic

In this topic, we cover 3 topics which are conventional vs spatial statistics, spatial statistics and GIScience, and nature of geospatial data. In conventional and spatial statistics, I learn about the meaning for both and why we used it in GIS. Conventional means that methods that we used directly applicable to the attribute components of spatial data. In spatial statistics, there were three of example that we used such as point, line, and polygon. Three of example can be used to distributions of data. Other than that, I learn about scale of measurements. For example, nominal, ordinal, interval, ratio and the example of four example.

Details

PROJEK RSS

PROJEK BERSAMA PIHAK JABATAN PERTANIAN BATU PAHAT

PROJEK BERSAMA PIHAK JABATAN PERTANIAN

Assalamualaikum saya ucapkan bagi pembuka kata tugasan refleksi projek bersama pihak Jabatan Pertanian Batu Pahat. Saya amat berbesar hati kerana projek yang diberikan oleh pensyarah sebulan yang lalu berjaya disempurnakan dengan baik. Semua ini tidak akan berjaya tanpa sokongan dan kerjasama rakan kumpulan saya dan pensyarah yang terlibat iaitu Dr Hawani dan Dr Faisal.

Saya sebenarnya tidak menyangka bahawa saya berjaya menyiapkan projek ini dan dibentangkan kepada Puan Normala iaitu wakil daripada Jabatan Pertanian Batu Pahat. Pada mulanya saya dan ahli kumpulan agak ragu-ragu untuk menyiapkan projek ini kerana keadaan semasa yang menyebabkan kami hanya mampu berhubung untuk berbincang mengenai projek menggunakan platform Google Meet.

Mengenai projek ini, kami ditugaskan untuk membantu pihak DOA menyelesaikan masalah yang mereka hadapi. Oleh itu, kami telah memilih tajuk “Senarai Pegawai APT Mengikut Kawasan Perkhidmatan”. Kami menggunakan data yang diberikan bagi menyelesaikan masalah tersebut. Dalam menyelesaikan projek ini, pembahagian tugas telah dilakukan. Setiap ahli telah dibahagikan dengan tugasan masing-masing tetapi kami tetap melakukan setiap tugasan itu bersama-sama. Walaupun setiap bahagian dilakukan bersama-sama, masalah ketika menjalankan projek itu masih ada. Misalnya, ada beberapa data koordinat yang diberikan tidak tertumpu pada kawasan yang betul. Oleh sebab itu, kami menggunakan pelbagai kaedah untuk mendapatkan koordinat yang betul. Contohnya, WGS84 Converter dan akhirnya kami mendapat koordinat di kawasan yang betul.

Apabila data yang diperolehi telah ditukarkan kepada format yang dikehendaki, saya sebagai kartografer telah memasukkan data tersebut ke dalam QGIS untuk proses membuat peta iaitu output yang akan dibentangkan kepada pensyarah dan pihak DOA. Dalam proses pembuatan peta, kami telah melakukan perjumpaan beberapa kali bagi menghasilkan output yang terbaik. Setiap ahli juga memberikan pendapat masing-masing. Akhirnya, output yang dihasilkan memuaskan hati setiap ahli kumpulan. Sebelum pembentangan dilakukan di hadapan pihak DOA, kami telah membentangkan projek di hadapan pensyarah kami terlebih dahulu dan kami menerima teguran dan telah membuat penambahbaikkan sebelum pembentangan dijalankan di hadapan Puan Normala menggunakan platform Webex.

Dengan selesainya pembentangan projek ini, ia menandakan bahawa selesainya tugasan projek yang diberikan oleh pensyarah kepada saya dan rakan-rakan yang lain. Tugasan projek ini  telah memberi saya satu pengalaman baru dalam mengendalikan satu tugasan yang besar. Walaupun pada mulanya saya agak risau tetapi akhirnya saya dan rakan kumpulan berjaya menyelesaikan projek ini dan ini merupakan satu kepuasan bagi saya dan penghargaan buat pensyarah dan rakan-rakan kumpulan saya. Sekian, terima kasih.

Screenshot (17).png.1

Details

About me

  • First name: NURINNAFISA BINTI MOHAMAD ZAKI
  • Student ID: A21BE0266
  • Display name: NURINNAFISA BINTI MOHAMAD ZAKI

NURINNAFISA BINTI MOHAMAD ZAKI's portfolios

NURINNAFISA BINTI MOHAMAD ZAKI's groups

NURINNAFISA BINTI MOHAMAD ZAKI's wall

No wall posts to display
View whole wall

NURINNAFISA BINTI MOHAMAD ZAKI's friends